Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
df_2007 = df[df['year'] == 2007]

fig = px.histogram(df_2007, x='pop', y='continent', color='continent',
                   text_auto='.2s', title='Population of different continents for the year 2007')

fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [4]:
fig = px.histogram(df_2007, x='pop', y='continent', color='continent',
                   text_auto='.2s', title='Population of different continents for the year 2007')

fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [5]:
fig = px.histogram(df_2007, x='pop', y='continent', color='continent',
                   text_auto='.2s', title='Population of different continents for the year 2007')

fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [6]:
fig = px.histogram(df, x='pop',
                   y='continent',
                   animation_frame='year',
                   color='continent',
                   range_x=[0, 4*10 ** 9], text_auto='.2s',
                   title='Population growth of the continents through the years')

fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')

fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [7]:
fig = px.histogram(df, 
                   x='pop', 
                   y='country', 
                   animation_frame='year', 
                   color='country', 
                   height=3000, 
                   range_x=[0,1.4*10**9])

fig.show()
In [ ]:
 

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [8]:
fig = px.histogram(df, 
                   x='pop', 
                   y='country', 
                   animation_frame='year', 
                   color='country', 
                   height=1000, 
                   range_x=[0,1.4*10**9])

fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [9]:
val_c = df.country.nunique()

fig = px.histogram(df, 
                   x='pop', 
                   y='country', 
                   animation_frame='year', 
                   color='country', 
                   range_x=[0,1.4*10**9], 
                   title='Popultion growth for the top 10 countries over the years')

fig.update_yaxes(categoryorder='total ascending')
fig.update_yaxes(range=(val_c - 10.5, val_c - 0.5))
fig.update_layout(showlegend=False)

fig.show()
In [ ]: